不同格式神经- tf方法在电磁参数化建模中的研究进展

2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM) Pub Date : 2021-11-28 DOI:10.1109/iwem53379.2021.9790626

Jinyuan Cui, Xiaoyu Wang, F. Feng, Shuxia Yan, Qi-jun Zhang

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摘要

神经- tf方法在电磁参数化建模中有着广泛的应用。本文综述了近年来基于神经tf的优化研究进展。本文提出了两种神经- tf方法，包括极点/残差格式的神经- tf方法和混合格式的神经- tf方法。通过耦合线滤波器和四极波导滤波器的两个参数化建模实例验证了这些方法的有效性。

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Recent Advances in Neuro-TF Methods with Different Format for EM Parametric Modeling

The neuro-TF methods are widely used for electromagnetic (EM) parametric modeling. The paper looks back the recent research progress in optimization based on the neuro-TF. Two neuro-TF methods we have proposed in the paper, include neuro-TF method with pole/residue format and neuro-TF method with hybrid format. The effectiveness of these methods are verified by two parametric modeling examples of a coupled-line filter and a four-pole waveguide filter.

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2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)

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